The recovery properties of nonconvex regularized M-estimators are analysed, under the general sparsity assumption on the true parameter. In the statistical aspect, the recovery bound for any ...stationary point of the nonconvex regularized M-estimator is established under some regularity conditions. In the computational aspect, the proximal gradient method is used to solve the nonconvex optimization problem and is proved to achieve a linear convergence rate, by virtue of a slight decomposition of the objective function. In particular, for commonly-used regularizers such as SCAD and MCP, a simpler decomposition is applicable thanks to the assumption on the regularizer, which helps to construct the estimator with better recovery performance. In the aspect of application, theoretical consequences are obtained on the corrupted error-in-variables linear regression model by verifying the required conditions. Finally, statistical and computational results as well as advantages of the assumptions are demonstrated by several numerical experiments. Simulation results show remarkable consistency with the theory under high-dimensional scaling.
•The recovery bound for the nonconvex regularized M-estimator is established.•Proximal gradient method is used and achieves a linear convergence rate.•Theoretical consequences are obtained on the corrupted linear regression model.•Numerical experiments demonstrate the statistical and computational results.
Multi-view Speech Emotion Recognition (SER) based on the pre-trained model has achieved success in speaker-independent scenarios. However, the existing SER methods rely on excessive feature views and ...have complicated feature fusion strategies. In this paper, we propose a novel method to learn effective emotion-related information from two feature views. First, we present a Discriminative Channel Weighting (DCW) module to weight the channel dimension of the features produced by a set of multi-scale convolution layers. This module allows for discriminative weighting of complex channel dimensions. Second, a concise Two-stream Pooling Attention (TsPA) strategy is proposed to generate two groups of fusion features based on different channel-level embeddings with different emphasis. Finally, the SER task is completed by three consecutive fully connected layers. The effectiveness of the proposed method has been demonstrated on two speaker-independent validation strategies, outperforming other state-of-the-art approaches.
Summary
Brassica napus (AACC, 2n = 38) is an important oilseed crop grown worldwide. However, little is known about the population evolution of this species, the genomic difference between its major ...genetic groups, such as European and Asian rapeseed, and the impacts of historical large‐scale introgression events on this young tetraploid. In this study, we reported the de novo assembly of the genome sequences of an Asian rapeseed (B. napus), Ningyou 7, and its four progenitors and compared these genomes with other available genomic data from diverse European and Asian cultivars. Our results showed that Asian rapeseed originally derived from European rapeseed but subsequently significantly diverged, with rapid genome differentiation after hybridization and intensive local selective breeding. The first historical introgression of B. rapa dramatically broadened the allelic pool but decreased the deleterious variations of Asian rapeseed. The second historical introgression of the double‐low traits of European rapeseed (canola) has reshaped Asian rapeseed into two groups (double‐low and double‐high), accompanied by an increase in genetic load in the double‐low group. This study demonstrates distinctive genomic footprints and deleterious SNP (single nucleotide polymorphism) variants for local adaptation by recent intra‐ and interspecies introgression events and provides novel insights for understanding the rapid genome evolution of a young allopolyploid crop.
The hexaploid species Echinochloa crus-galli is one of the most detrimental weeds in crop fields, especially in rice paddies. Its evolutionary history is similar to that of bread wheat, arising ...through polyploidization after hybridization between a tetraploid and a diploid species. In this study, we generated and analyzed high-quality genome sequences of diploid (E. haploclada), tetraploid (E. oryzicola), and hexaploid (E. crus-galli) Echinochloa species. Gene family analysis showed a significant loss of disease-resistance genes such as those encoding NB-ARC domain-containing proteins during Echinochloa polyploidization, contrary to their significant expansionduring wheat polyploidization, suggesting that natural selection might favor reduced investment in resistance in this weed to maximize its growth and reproduction. In contrast to the asymmetric patterns of genome evolution observed in wheat and other crops, no significant differences in selection pressure were detected between the subgenomes in E. oryzicola and E. crus-galli. In addition, distinctive differences in subgenome transcriptome dynamics during hexaploidization were observed between E. crus-galli and bread wheat. Collectively, our study documents genomic mechanisms underlying the adaptation of a major agricultural weed during polyploidization. The genomic and transcriptomic resources of three Echinochloa species and new insights into the polyploidization-driven adaptive evolution would be useful for future breeding cereal crops.
This study reports high-quality genome sequences of hexaploid Echinochloa crus-galli and its progenitor Echinochloa oryzicola (tetraploid) and a diploid species (Echinochloa haploclada). By comparing the gene family expansion, subgenome evolution, and transcriptomic changes during hexaploidization between E. crus-galli and bread wheat, the authors uncover different patterns of genome evolution during polyploidization of an agricultural weed and a crop.
After renal transplant, immunosuppression therapy is used to reduce the risk of rejection. Here, we describe the case of an adult living related donor renal transplant recipient with rare natural ...chimerism, as discovered by short tandem repeat sequence analysis. In our process of matching transplant patients, we perform human leukocyte antigen testing and short tandem repeat chimerism testing to decide postoperative immunosuppression strategy for transplant patients. We analyzed the short tandem repeat chimerism status before renal transplant and determined that this patient represented a rare case of natural chimerism. Assessment of organ recipient chimerism can inform physicians regarding a dosage reduction of immunosuppressive agents. Short tandem repeat sequence analysis provides substantial information regarding existing polymorphisms and can identify chimerism, if present, and thereby guide immunosuppression strategies after renal transplant, which may improve the long-term immunosuppression-free survival of renal transplant recipients.
Speech emotion recognition (SER) based on multi-view learning has made some progress on speaker-independent scenarios. How-ever, the existing SER methods always rely on excessive feature views and ...ignore the importance of heterogeneous feature learning. In this paper, we propose a novel multi-level attention method to effectively learn the heterogeneous information from the hand-crafted feature (MFCC) and the feature (W2V2) extracted from the pre-trained model. Specifically, we first design an Attention based Multi-scale Low-level Feature (A-MLF) extractor to extract scale-specific emotion-related regions from MFCC. Then, the Multi-Unit Attention (MUA) module is used to simultaneously learn discriminative features in three different dimensions. Finally, a two-stage feature fusion strategy is used for joint representation space learning. We demonstrate our method on two speaker-independent validation strategies and interpret the SOTA performance by visualizing the feature distribution.
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